Operations | Monitoring | ITSM | DevOps | Cloud

Being responsible for the reliability of services people count on every day isn’t easy. Customers expect everything to work, all the time, and when it doesn’t, someone has to answer for it. Whether you need to get yourself out of bed at 3 a.m. or step away from a family dinner, your job is to quickly diagnose the problem and fix it to ensure your operations get back up and running quickly before customers notice. But it doesn’t always go like that.

Today, we’re introducing Paige, PagerDuty’s SRE Agent. Built on over 16 years of operational data, Paige works as a member of operations, engineering, and DevOps teams, coordinating signal intelligence, incident management, and automation. Paige learns from every incident, so every incident improves the next response. Each resolution is written back into shared memory, making every response sharper than the last.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s Runbook Automation / Rundeck MCP Server recently announced in GA builds towards this vision.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s AI-Powered Incident Communications builds towards this vision.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PagerDuty’s PagerDuty Docs recently announced in builds towards this vision. Documentation is the living manual for any product. Over 68% of developers still turn to docs first when learning a new tool, and 84% now use an AI tool daily. Those two numbers together change what documentation is for.

AI adoption is now a measurable driver of both uptime and growth. According to PagerDuty’s 2026 State of AI-First Digital Operations report, 75% of organizations actively incorporating AI into digital operations claim to have improved operational resilience and maturity over the past year. The same report suggests AI in operations is also a revenue driver.

Most organizations managing major incidents realized that every moment matters. Context-switching between different tools – with multiple web and chat surfaces having to be open to collect information causes friction. The cost of context-switching during an outage is even more painful. These are the problems that PagerDuty’s Slack Transformation just closed.

PagerDuty’s new intelligent Model Context Protocol (MCP) tools, recently announced in Early Access, are a step toward autonomous operations. Here’s how they help customers get there.

According to a 2025 report from Ravio, entry-level hiring (especially in engineering roles) has collapsed by more than 73% due to increasing AI capabilities. That means junior developer jobs are disappearing. At the same time, demand for senior engineers keeps climbing because organizations need more people to manage and optimize their complex AI agents.

This blog post is part of PagerDuty’s ongoing series on how we’re helping customers navigate their journey towards autonomous operations. Read on to learn about how PD Automation Runner, now in Early Access, builds towards this vision. Your on-call engineer gets paged for a critical alert on a self-hosted Kubernetes cluster. If this were a cloud-hosted service, Workflow Actions and the SRE Agent would already be working the problem: pulling logs, checking health, surfacing a fix.